PROJECT SUMMARY/ABSTRACT (DESCRIPTION) The objective of this proposal is to implement, assess, and enhance a novel technology that can automatically obtain patient photographs at the point-of-care of medical imaging and thus provide a biometric identifier to prevent wrong-patient errors. Wrong-patient errors in radiology, where one patient's medical imaging study is erroneously placed in another patient's record in the picture archiving and communications system (PACS), can cause serious complications for both involved patients. Despite the use of the Joint Commission mandated dual-identifier technique, wrong-patient errors continue to occur. Patient facial photographs obtained at the point-of-care of medical imaging can serve as biometric identifiers that are easily obtained, intrinsic, yet externally visible and non-obtrusively obtained. Prior work by the investigators has demonstrated that such photographs can significantly increase the detection of simulated wrong-patient errors in pre-clinical observer studies. Competing technologies such as fingerprint identifiers, palm vein mapping or retinal scanning, while using intrinsic identifiers, are obtrusive; other technologies that rely on patient armbands with barcodes, while nonobtrusive, only provide extrinsic identifiers that are not unique to the patient. CameRad Technologies, LLC is developing this technology?the PatCamTM system, with two main components, a camera device and an integration server. The integration server accurately matches the photographs with the correct medical imaging studies and then stores them together in the PACS. In this proposal, CameRad will pursue the following aims to de-risk the technology on the path to commercialization. In Aim 1, the investigators will demonstrate that their technology is vendor-neutral and can operate in a highly secure, controlled environment, by implementing the system at the Veterans Affairs Maryland Healthcare System's (VAMHCS) McKesson PACS. They will then assess whether the technology can increase error detection, decrease interpretation time, and be perceived favorably by radiologists in a clinical setting at VAMHCS. In Aim 2, CameRad will develop an automated system face verification system for flagging potentially misidentified imaging studies for review by humans. Achievement of these aims are critical in preparation for a Phase II SBIR project, which will involve a multi-center clinical workflow study to demonstrate that patient photographs can 1) increase detection of wrong patient errors clinically and 2) increase radiologist interpreter efficiency. Most importantly, the potential future impact of this technology is that it can personalize medical imaging studies thereby increasing the focus of interpreting physicians.